{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:ZIDM5G2SPZLW63MAOALAZ3FRMX","short_pith_number":"pith:ZIDM5G2S","canonical_record":{"source":{"id":"2510.20441","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SD","submitted_at":"2025-10-23T11:22:24Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"51bc667ea594b2aaea89e06b4f0b57d8970b775450761fb8eada054a0526854c","abstract_canon_sha256":"08407cbbbe0d47ecc51b1bce28a0e327d9bd8e4f150457aeab632b41623e4b94"},"schema_version":"1.0"},"canonical_sha256":"ca06ce9b527e576f6d8070160cecb165fc547da261485aefb0afdb3008185b01","source":{"kind":"arxiv","id":"2510.20441","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2510.20441","created_at":"2026-07-03T01:17:14Z"},{"alias_kind":"arxiv_version","alias_value":"2510.20441v2","created_at":"2026-07-03T01:17:14Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2510.20441","created_at":"2026-07-03T01:17:14Z"},{"alias_kind":"pith_short_12","alias_value":"ZIDM5G2SPZLW","created_at":"2026-07-03T01:17:14Z"},{"alias_kind":"pith_short_16","alias_value":"ZIDM5G2SPZLW63MA","created_at":"2026-07-03T01:17:14Z"},{"alias_kind":"pith_short_8","alias_value":"ZIDM5G2S","created_at":"2026-07-03T01:17:14Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:ZIDM5G2SPZLW63MAOALAZ3FRMX","target":"record","payload":{"canonical_record":{"source":{"id":"2510.20441","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SD","submitted_at":"2025-10-23T11:22:24Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"51bc667ea594b2aaea89e06b4f0b57d8970b775450761fb8eada054a0526854c","abstract_canon_sha256":"08407cbbbe0d47ecc51b1bce28a0e327d9bd8e4f150457aeab632b41623e4b94"},"schema_version":"1.0"},"canonical_sha256":"ca06ce9b527e576f6d8070160cecb165fc547da261485aefb0afdb3008185b01","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-03T01:17:14.169062Z","signature_b64":"zcHoGtSQ3kT9+EzE4N+FAd0XVc7ohZQaReTFt5yaYkUmZjsDmmJ5zUEouMj7v1DsGSKoyo4NipeUerP+dxKADQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"ca06ce9b527e576f6d8070160cecb165fc547da261485aefb0afdb3008185b01","last_reissued_at":"2026-07-03T01:17:14.168551Z","signature_status":"signed_v1","first_computed_at":"2026-07-03T01:17:14.168551Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2510.20441","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-03T01:17:14Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"EBrCMpKqco7z+kpTq2BFtB+BARFokNTFDKrxJjMPthrMrrwlNzSjKgijgtO3kiBGPjqdW2vbgDhBB3Mq9U0gAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-04T11:01:23.661007Z"},"content_sha256":"c585f92dca0d92aaeece38f75b67f03499e599f98a986889f9fc81e34cfaca4e","schema_version":"1.0","event_id":"sha256:c585f92dca0d92aaeece38f75b67f03499e599f98a986889f9fc81e34cfaca4e"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:ZIDM5G2SPZLW63MAOALAZ3FRMX","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"UniSE: A Unified Framework for Decoder-Only Autoregressive LM-Based Speech Enhancement","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.SD","authors_text":"Chengwei Liu, Haoyin Yan, Shaofei Xue, Xiaotao Liang, Yinghao Liu, Yuxiang Kong, Zheng Xue","submitted_at":"2025-10-23T11:22:24Z","abstract_excerpt":"Neural audio codecs have largely promoted the application of language models (LMs) for speech applications. However, the effectiveness of autoregressive LM-based models in unifying speech enhancement (SE) tasks remains underexplored. In this work, we propose UniSE, a unified decoder-only LM-based framework to handle different SE tasks including speech restoration, target speaker extraction, and speech separation. Conditioned on input speech features, it autoregressively generates target discrete tokens, facilitating compatibility between distinct learning patterns of multiple tasks. To further"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2510.20441","kind":"arxiv","version":2},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2510.20441/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-03T01:17:14Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"kyN+QxbYPezQ3w2+hG++ht+c968OguKsV+alC5vSZXssoso2k76XZY0dtELOsLHxJ0+BA4FqOfTecn++MwdADA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-04T11:01:23.661394Z"},"content_sha256":"5862f3b4557672bc4719a7794747bb375b77a39a85a7dd06fb8d1f3bb8fdd29c","schema_version":"1.0","event_id":"sha256:5862f3b4557672bc4719a7794747bb375b77a39a85a7dd06fb8d1f3bb8fdd29c"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/ZIDM5G2SPZLW63MAOALAZ3FRMX/bundle.json","state_url":"https://pith.science/pith/ZIDM5G2SPZLW63MAOALAZ3FRMX/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/ZIDM5G2SPZLW63MAOALAZ3FRMX/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-07-04T11:01:23Z","links":{"resolver":"https://pith.science/pith/ZIDM5G2SPZLW63MAOALAZ3FRMX","bundle":"https://pith.science/pith/ZIDM5G2SPZLW63MAOALAZ3FRMX/bundle.json","state":"https://pith.science/pith/ZIDM5G2SPZLW63MAOALAZ3FRMX/state.json","well_known_bundle":"https://pith.science/.well-known/pith/ZIDM5G2SPZLW63MAOALAZ3FRMX/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:ZIDM5G2SPZLW63MAOALAZ3FRMX","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"08407cbbbe0d47ecc51b1bce28a0e327d9bd8e4f150457aeab632b41623e4b94","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SD","submitted_at":"2025-10-23T11:22:24Z","title_canon_sha256":"51bc667ea594b2aaea89e06b4f0b57d8970b775450761fb8eada054a0526854c"},"schema_version":"1.0","source":{"id":"2510.20441","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2510.20441","created_at":"2026-07-03T01:17:14Z"},{"alias_kind":"arxiv_version","alias_value":"2510.20441v2","created_at":"2026-07-03T01:17:14Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2510.20441","created_at":"2026-07-03T01:17:14Z"},{"alias_kind":"pith_short_12","alias_value":"ZIDM5G2SPZLW","created_at":"2026-07-03T01:17:14Z"},{"alias_kind":"pith_short_16","alias_value":"ZIDM5G2SPZLW63MA","created_at":"2026-07-03T01:17:14Z"},{"alias_kind":"pith_short_8","alias_value":"ZIDM5G2S","created_at":"2026-07-03T01:17:14Z"}],"graph_snapshots":[{"event_id":"sha256:5862f3b4557672bc4719a7794747bb375b77a39a85a7dd06fb8d1f3bb8fdd29c","target":"graph","created_at":"2026-07-03T01:17:14Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2510.20441/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Neural audio codecs have largely promoted the application of language models (LMs) for speech applications. However, the effectiveness of autoregressive LM-based models in unifying speech enhancement (SE) tasks remains underexplored. In this work, we propose UniSE, a unified decoder-only LM-based framework to handle different SE tasks including speech restoration, target speaker extraction, and speech separation. Conditioned on input speech features, it autoregressively generates target discrete tokens, facilitating compatibility between distinct learning patterns of multiple tasks. To further","authors_text":"Chengwei Liu, Haoyin Yan, Shaofei Xue, Xiaotao Liang, Yinghao Liu, Yuxiang Kong, Zheng Xue","cross_cats":["cs.AI"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SD","submitted_at":"2025-10-23T11:22:24Z","title":"UniSE: A Unified Framework for Decoder-Only Autoregressive LM-Based Speech Enhancement"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2510.20441","kind":"arxiv","version":2},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:c585f92dca0d92aaeece38f75b67f03499e599f98a986889f9fc81e34cfaca4e","target":"record","created_at":"2026-07-03T01:17:14Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"08407cbbbe0d47ecc51b1bce28a0e327d9bd8e4f150457aeab632b41623e4b94","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SD","submitted_at":"2025-10-23T11:22:24Z","title_canon_sha256":"51bc667ea594b2aaea89e06b4f0b57d8970b775450761fb8eada054a0526854c"},"schema_version":"1.0","source":{"id":"2510.20441","kind":"arxiv","version":2}},"canonical_sha256":"ca06ce9b527e576f6d8070160cecb165fc547da261485aefb0afdb3008185b01","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"ca06ce9b527e576f6d8070160cecb165fc547da261485aefb0afdb3008185b01","first_computed_at":"2026-07-03T01:17:14.168551Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-03T01:17:14.168551Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"zcHoGtSQ3kT9+EzE4N+FAd0XVc7ohZQaReTFt5yaYkUmZjsDmmJ5zUEouMj7v1DsGSKoyo4NipeUerP+dxKADQ==","signature_status":"signed_v1","signed_at":"2026-07-03T01:17:14.169062Z","signed_message":"canonical_sha256_bytes"},"source_id":"2510.20441","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:c585f92dca0d92aaeece38f75b67f03499e599f98a986889f9fc81e34cfaca4e","sha256:5862f3b4557672bc4719a7794747bb375b77a39a85a7dd06fb8d1f3bb8fdd29c"],"state_sha256":"103e3eb56c45499bdd8887e029677a8907bf225a40b663105e115f0fd07358d2"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"kWJIWryKQlBsOW9IJSffGzem44kwZt3pdcDnf7rgjXzl3Aci9VrnABR2+AOr0+KP72m3bK7ZyHHUcliaV7c3Bg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-04T11:01:23.663386Z","bundle_sha256":"b443308417071fd50e1890b42e2c8cb2b4642ee4c7bd3e940b08747628a04b96"}}